Digital Commons Network^™

The Nested Dirichlet Process And Applications To Nonparametric Bayesian Inference, Evan C. Donald

Graduate Thesis and Dissertation post-2024

This body of research focuses on Bayesian nonparametric inference, in regards to an array of S-valued random variables. These random variables are assumed to take values in a complete and separable metric space and further have a particular symmetry property, row exchangeability.

The Nested Dirichlet Process is a particularly apt model for inference in such circumstances. However, calculating posterior distributions in this framework is exceedingly difficult, and become exponentially more complicated as sample size increases.

This research explores the method of using sequential imputation to calculate posterior distributions, providing a rigorous proof of the method’s suitability that had been missing …

Numerical Solutions For Deterministic And Stochastic Partial Differential Equations And Effective Integral Evaluation, Guanqian Wang

Graduate Thesis and Dissertation post-2024

This thesis explores advancements in numerical methods, focusing on their applications to some classes of PDEs, Stochastic PDEs (SPDEs), and integral evaluations. The first part of this proposal provides algorithms for computing the mean curvature flow, including cases with topological changes. We propose energy-penalized and multilevel minimization algorithms. Benchmark problems with random initial conditions reveal that small changes in interaction length led to different solution patterns under topological changes. Our methods demonstrate robustness and efficiency, even with poor initial guesses, making them suitable for a wide range of scenarios.

The second part of this proposal introduces a new approach for …

Positivity And Invariance: From Radial Basis Functions To Graph Signal Spaces, Seok-Young Chung

Graduate Thesis and Dissertation post-2024

This dissertation investigates the positivity problem and zero localization of special functions or integral transforms, with particular emphasis on their implications in analysis, approximation theory, and signal processing. The first half centers on the characterization of positive definite radial functions via Hankel transforms involving Bessel functions. Motivated by classical results such as Bochner's theorem and Schoenberg’s work, we examine analytic conditions under which these transforms remain nonnegative, thereby ensuring the positive definiteness of radial basis functions (RBFs). We then explore the transition beyond positivity by focusing on the reality of zeros in Hankel (or Fourier) transforms. This leads to two …

Viability For Locally Monotone Evolution Inclusions And Lower Semicontinuous Solutions Of Halmilton-Jacobi-Bellman Equations In Infinite Dimensions, Jichao Jiang

Graduate Thesis and Dissertation post-2024

In this thesis we first study the necessary and sufficient conditions for differential inclusion driven by locally monotone operator in the sense of Liu and Röckner [J. Funct. Anal., 259 (2010), pp. 2902-2922]. The main result of our work provides a necessary and sufficient condition for a set K being viable, that is, a solution of the differential inclusion stay inside of the set K through out the time interval. We then examine the path-dependent Hamilton-Jacobi-Bellman equations (path-dependent HJB equations) associated to the optimal control problem with states controlled by evolution inclusions. With our results on viability, we …

Self Advection Of A Thin Vortex Filament In Incompressible Fluid, Gayathri Krishnan

Graduate Thesis and Dissertation post-2024

This thesis explores the self advection of a thin vortex filament in an incompressible fluid. The effect of slipping motion on the filament caused by viscosity is investigated. This problem is addressed by working with three models developed for this purpose.

The Da Rios-Betchov equations are obtained from the expression for the velocity of the vortex filament under the assumptions of local induction approximation. They describe the evolution of the intrinsic geometric quantities, namely, curvature and torsion of the filament. The invariants associated with these equations are deduced. The linear instability of the vortex filament motion obtained by Betchov is …

Advanced Subspace Estimation Techniques For Statistical Analysis And Machine Learning, Kang Li

Graduate Thesis and Dissertation post-2024

The rapid expansion of data volume and complexity across diverse domains has underscored the need for robust and efficient techniques capable of extracting meaningful information from high-dimensional datasets. Subspace estimation—identifying the underlying low-dimensional structures within high-dimensional data—has emerged as a cornerstone method in modern data analysis and machine learning. This dissertation aims to advance both the theoretical and practical aspects of subspace estimation problems.

In the first part, we investigate Fréchet central subspace estimation, a critical component of sufficient dimension reduction (SDR) challenges. Traditional SDR methods often fall short when dealing with non-Euclidean responses. To address this, we propose a …

Carleman Linearization Of Dynamical Systems, And Graph Inverse And Wiener Filtering, Cong Zheng

Graduate Thesis and Dissertation post-2024

Carleman linearization is a mainstream approach for transforming finite-dimensional nonlinear dynamical systems into infinite-dimensional linear systems. It provides accurate approximations of the original nonlinear system over larger regions around the equilibrium for longer time horizons, surpassing the capabilities of conventional first-order linearization. In Chapter 1, we derive explicit error bounds for the finite-section approximation, demonstrating its exponential convergence concerning the finite-section order. We illustrate that for a specific class of nonlinear systems, exponential convergence can be achieved across the entire time horizon, extending to infinity. These results hold significant practical utility, as the proposed error bounds can be used to …

Robust Evaluation Framework On Adversarial Purification, Yuan Du

Graduate Thesis and Dissertation post-2024

This dissertation proposes novel Energy-Based Model (EBM) learning strategies and adversarial robustness evaluation framework that addresses critical gaps in iterative purification defenses. First, we introduce strategies to learn EBMs by controlling MCMC sampling trajectory lengths for distinct applications: (i) short-run sampling for state-of-the-art unconditional image generation on CIFAR-10 and ImageNet; (ii) mid-run sampling for classifier-agnostic adversarial purification; and (iii) long-run sampling for principled density modeling. Using three novel MCMC initialization techniques within standard Maximum Likelihood objectives, we enable significant performance gains without architectural modifications. Second, we address evaluation deficiencies in existing iterative stochastic defenses by developing the \textit{Memory Efficient Full-gradient …

Organization And Activation Of Caffeine Expectancies, Catherine S. Forsyth

Honors Undergraduate Theses

Caffeine is the most consumed and widely used psychoactive substance in the world. Whether someone uses caffeine or not, expectations about use can be influential to some degree. Expectancies exist everywhere and are extremely influential in all aspects of life. Regarding drug use, expectancies can affect behavior, outcomes, and one’s experience with the drug. Caffeine is no exception, caffeine expectancies have been seen to play a role in several actions such as the development, maintenance, and reinforcement of caffeine use. This study examined latent use profiles of caffeine and relationships between the profiles and the activation of caffeine expectancies. Multidimensional …

Generation Z’S Perception Of Skin Cancer And How It Relates To Climate Change, Piercen Bogolea

Honors Undergraduate Theses

Skin cancer is the most common cancer worldwide, and climate change has been identified as a significant contributor. Preventative action early on can help reduce occurrence, but it is unknown if Generation Z is aware of this and is taking the necessary action now to protect themselves. This research aims to gauge the perception of Generation Z on the severity of skin cancer, the relationship between climate change and skin cancer, and the prevalence of preventative measures being taken. A survey was distributed to students aged 18 to 27 enrolled at the University of Central Florida through mixed sampling. The …

Rhythm Against Poethics, Jayvyn Dacas

Honors Undergraduate Theses

This thesis stages an auto-poetic ethnography that listens to, and moves with, the anterior spaces of Black life. Those murmurs, hums, musical hesitations, and infrastructural vibrations that refuse capture by dominant epistemic regimes. Drawing from Ramon Amaro’s reading of Sylvia Wynter, Katherine McKittrick and Alexander Weheliye’s reflections on sound, Fred Moten’s insights on displacement, and Tendayi Sithole’s attention to the phonographic, the project situates music production as method and unworlding. Through engagements with the 808, sampling, sound systems, and embodied listening across Florida. Spaces like the warehouse, the party, record stores, and community become the work of Black voices, and …

Exploring Electroweak Baryogenesis Within Real Scalar Models: Theoretical Foundations And Collider Phenomenology, Corine M. Smith

Honors Undergraduate Theses

The matter–antimatter asymmetry and the hierarchy problem related to the Higgs boson mass remain key open questions in high energy physics. Electroweak Baryogenesis offers a solution to the asymmetry by modifying the Higgs sector to allow a strongly first-order phase transition. This work investigates two real singlet scalar extensions of the Standard Model, incorporating novel quartic and triple couplings between the new scalar fields, providing a testable framework for vacuum-induced scalar mixing effects and enhanced multi-Higgs boson production. These interactions modify the scalar self-coupling and can induce resonant enhancements in multi-Higgs boson production processes. The theoretical constraints are derived from …

Math Escape Room: A Virtual/Blended Problem‑Solving Adventure, Youssef Ibrahim

Teaching Online Pedagogical Repository

A narrative‑driven digital escape room turns secondary‑level mathematics review into a collaborative quest: students unlock successive “rooms” by solving algebraic, geometric, and data‑analysis challenges in Google Forms and Genially. Timers, conditional branching, and embedded hints sustain flow, while instructor analytics reveal misconceptions in real time.

Taiwanese Elementary School Teachers’ Mindset Of Content And Language Integrated Learning (Clil) Instruction, Chin-Wen Chien

Journal of English Learner Education

Teachers need to undergo a mindset shift in language learning and teaching. This study used both qualitative and quantitative data to explore seven Taiwanese Content and language integrated learning (CLIL) teachers’ mindsets and led to the following major findings. First, the CLIL teachers had a stronger mindset regarding their instructional strategies, lesson preparations, and efficacy, compared to their more moderate mindset regarding their CLIL training and preparation. Secondly, the CLIL teachers had a different mindset regarding language use in their CLIL instruction due to their learners’ English proficiency levels. Finally, their lesson designs were lacking a 4Cs culture. Based on …

Digital Stories Of Resilience: A Case Study Of Urban Community College English Learners, Patricia George Hunter

Journal of English Learner Education

This study utilizes a qualitative case study approach to learn how project-based, digital storytelling (DST) voices the resilience of post-secondary English language learners (ELLs) attending a minority-serving, open-access, community college in New York City. Along with many studies that have examined the usefulness of DST in oral production, this research investigates whether project-based digital storytelling enhances students’ understanding of academic content related to resilience and conventional composition. Narrative inquiry (NI) research technique is the basis of the digital story project in an English as a Second Language (ESL) course. In this case, the study relies on observations and artifacts to …

Now I See: Video Supports For English Language Learners, Joanna C. Zimmerle, Hanrui He, Tara Hill

Journal of English Learner Education

General education teachers are often unprepared by teacher preparation programs and limited professional development opportunities to support English Language Learners (ELLs), despite the increasing number of ELLs entering US schools and the trend towards placing them in mainstream classrooms. Video resources offer one viable approach to supporting the language learning of ELLs, drawing upon theoretical frameworks such as dual-coding, constructivist theory, and sociocultural perspectives. This paper describes the use of video resources to assist general education teachers in effectively leveraging videos to support the language learning of ELLs in mainstream classrooms.

A Systematic Review Of The Effects Of Ai-Assisted Moderation On Individuals And Groups, Zehui Yu, Lukas Otto, Dennis Assenmacher, Claudia Wagner

Human-Machine Communication

This review paper provides a conceptualization of AI-assisted content moderation with various degrees of autonomy and summarizes experimental evidence for how different levels of automation in content moderation and related losses of autonomy affect individuals and groups. Our results show that current research predominantly focuses on individuallevel effects, necessitating a shift toward understanding the impact on groups. The study highlights gaps in exploring different levels of AI-assisted moderation interventions and misalignments of different conceptualizations that make comparing research results difficult. The discussion underscores the prevailing emphasis on harmful content removal and advocates for investigating more constructive moderation techniques, emphasizing the …

Ucf Pegasus Plan - Kindergarten - Importance Of Rules And Laws, Angelica F. Bryan, Juanita White

Pegasus Plans: Social Studies Unit Plans for Florida Teachers

During this unit, students will compare rules and laws, explore rules at school and home through role playing activities, and explore laws made for the community. Students will learn about the roles that individuals play in making or following rules and laws at school, home and in the community.

University Of Central Florida Undergraduate Catalog, 2024 - 2025, University Of Central Florida

UCF Catalogs

No abstract provided.

Transforming Libraries Through Engagement: Lessons From A Library Ai Interest Group, Lily Dubach, Rachel Vacek

Faculty Scholarship and Creative Works

Learn how one academic library is engaging with its employees to explore the latest trends, tools, and topics in AI through an interest group (IG). Through stimulating discussions, webinars, guest speakers, demos, and sharing of experiences with AI, the IG empowers its library community to explore and become more comfortable with AI. This session caters to varying levels of AI expertise. Challenges, successes, and valuable insights for deeper engagement will be shared so you can learn how to establish a similar initiative in your library.

Teaching English Language Learners: Exploring The Instructional Modifications Mainstream Teachers Use, Nilufer Guler

Journal of English Learner Education

The number of language learners (ELLs) is increasing rapidly at U.S. schools. Mainstream teachers have an important role in the academic success of these students because ELLs spend most of their school time in mainstream classes and are pulled out a few hours in a school day for ELL services. This research aims to uncover the educational experiences of ELLs in mainstream classes. Using statewide systematic initiative and qualities of linguistically responsive teachers as theoretical frameworks, I collected survey data from 129 teachers and interviewed 15 teachers. The results have shown that teachers tend to translate language for their students …

Cooperating Teachers’ Views And Practices About Teaching Emergent Bilinguals In General Education Classrooms, Tunde Szecsi, Janka Szilagyi

Journal of English Learner Education

Cooperating teachers’ pedagogical beliefs and practices influence teacher candidates’ views and practices. Therefore, this study examined mainstream cooperating teachers’ perceptions about critical components of effective instruction for English learners, and the relationship between these teachers’ perceptions and classroom practices. We interviewed 55 teachers and completed a 90-minute observation in each classroom. We analyzed the interviews for common themes, and we used descriptive statistics to summarize the observation data. The findings indicated that teachers were well-versed in evidence-based instructional activities and strategies. However, many teachers found it challenging to infuse ELs’ language, culture and experiential background into their instruction.

Addressing Language And Content In Civics Through A Language-Based Approach To Content Instruction For Multilingual Learners, Jia Gui, Luciana C. De Oliveira

Journal of English Learner Education

This study explores the integration of a language-based approach to content instruction’s (LACI) six Cs of support into an existing civics lesson plan to improve content and language learning for multilingual learners. We used the Civics for All curriculum from the New York City Department of Education to identify lesson plans that could be enhanced for teaching multilingual learners. The findings of integrating the LACI framework indicated that the existing lesson plans could be enhanced by adding all the Cs to ensure full support for multilingual learners. We conclude with strategies for integrating the LACI framework into existing civics lesson …

Human-Machine Communication: Complete Volume. Volume 8

Human-Machine Communication

This is the complete volume of HMC Volume 8.

Machine Ex Machina: A Framework Decentering The Human In Ai Design Praxis, Cait Lackey, Zizi Papacharissi

Human-Machine Communication

Artificial intelligence (AI) design typically incorporates intelligence in a manner that is affirmatory of the superiority of human forms of intelligence. In this paper, we draw from relevant research and theory to propose a social-ecological design praxis of machine inclusivity that rejects the presumption of primacy afforded to human-centered AI. We provide new perspectives for how human-machine communication (HMC) scholarship can be synergistically combined with modern neuroscience’s integrated information theory (IIT) of consciousness. We propose an integrated theoretical framework with five design practice recommendations to guide how we might think about responsible and conscious AI environments of the future: symbiotic …

Cyberbullying Detection On Twitter Data Using Machine Learning Classifiers, Pradip Dhakal

Data Science and Data Mining

This study compares some of the popular machine learning techniques like Logistic Regression, Multinomial Naive Bayes, K-Nearest Neighbor, and Extreme Gradient Boosting to classify the tweets into three different categories: cyberbullying based on religion, cyberbullying based on ethnicity, or no cyberbullying. First, various data-cleaning approaches are used to clean the tweet data. After the data is clean and ready, the word embedding techniques, such as a bag of words and term frequency-Inverse document frequency, are used to convert the words into mathematical vectors. Finally, the model will be fitted using the combination of the above-mentioned word embedding techniques and machine …

Enhancing Experience Through The Integration Of Demonstrations And Simulations, Michael Mckenzie, Amy Mckenzie

Teaching Online Pedagogical Repository

This strategy utilizes demonstrations and simulations in an online environment to improve student engagement. It first explains the literature behind demonstrations/simulations and then provides the reader with a plan to implement and examples to reference.

Artificial Sociality, Simone Natale, Iliana Depounti

Human-Machine Communication

This article proposes the notion of Artificial Sociality to describe communicative AI technologies that create the impression of social behavior. Existing tools that activate Artificial Sociality include, among others, Large Language Models (LLMs) such as ChatGPT, voice assistants, virtual influencers, socialbots and companion chatbots such as Replika. The article highlights three key issues that are likely to shape present and future debates about these technologies, as well as design practices and regulation efforts: the modelling of human sociality that foregrounds it, the problem of deception and the issue of control from the part of the users. Ethical, social and cultural …

The Perturbing Mediatization Of Voice-Based Virtual Assistants: The Case Of Alexa, Leopoldina Fortunati, Autumn P. Edwards, Chad Edwards

Human-Machine Communication

This study examines the role of voice-based assistants (VBAs), specifically Alexa, in the mediatization paradigm framework. The authors hypothesize that emerging technologies such as chatbots and VBAs intensify the process of online meta-reintermediation of news. Three research questions were investigated through a questionnaire administered to 655 university students in the US and Italy: Do participants try to get news from Alexa? Are participants aware that VBAs represent a case of meta-reintermediation of news? Does Alexa contribute to the potential hybridization of news, information, and knowledge? The analysis of 451 open-ended answers showed that only a fraction of participants searches for …

Communicative Ai And Techno-Semiotic Mediatization: Understanding The Communicative Role Of The Machine, Göran Bolin

Human-Machine Communication

Mediatization discourse has so far mainly been centered on media from institutional or social-constructionist approaches. The technological developments within communications industries coupled with the wider societal process of datafication might, however, beg for dusting off the smaller, although the long-time existing, technological approach to mediatization as a complement to the two other approaches, in order to understand aspects of automation and human-machine communication. This theoretical article explores how existing mediatization approaches can refocus to include lessons learned from human-machine communication. The first section accounts for the main mediatization approaches. The second section discusses debates on communication, artificiality, and meaning-making. The …